Edureka

SEPTEMBER 11, 2023

Businesses have more data than ever, including how customers interact with them and what they do on social media, as well as how much inventory they have and how much money they make. In this situation, Business Intelligence (BI) platforms become an important way to make sense of all this data. How to Pick the Right BI Platform?

Business Intelligence 52

Business Intelligence BI Database-centric Raw Data 52

Knowledge Hut

APRIL 25, 2024

However, with Business intelligence dashboards, knowledge is dispersed throughout the organization, enabling users to produce interactive reports, utilize data visualization, and disseminate the knowledge with internal and external stakeholders. What is a Business Intelligence Dashboard?

Business Intelligence 52

Business Intelligence BI Raw Data Data Warehouse 52

Knowledge Hut

JANUARY 19, 2024

The key has the right tools, starting with knowing what data is important for your business. Business intelligence (BI) and business analytics (BA) are two terms that are often used interchangeably, but there is some important difference between business intelligence and business analytics.

Business Intelligence 52

Business Intelligence BI Business Analyst Aggregated Data 52

Ascend.io

OCTOBER 28, 2024

Filling in missing values could involve leveraging other company data sources or even third-party datasets. Data Normalization Data normalization is the process of adjusting related datasets recorded with different scales to a common scale, without distorting differences in the ranges of values.

Raw Data 52

Raw Data Datasets Aggregated Data Data Pipeline 52

Edureka

JANUARY 2, 2025

Microsoft created Power BI , a quickly expanding business intelligence (BI) tool and data visualization program, to revolutionize how businesses use data analytics to address business issues. You will often need to work around several features to get the most out of business data with Microsoft Power BI.

BI 52

BI Datasets Business Intelligence Data Analysis 52

DataKitchen

NOVEMBER 5, 2024

Data is typically organized into project-specific schemas optimized for business intelligence (BI) applications, advanced analytics, and machine learning. The Medallion architecture is a framework that allows data engineers to build organized and analysis-ready datasets in a lakehouse environment.

Architecture 78

Architecture Raw Data Pipeline-centric Data Ingestion 78

Striim

APRIL 18, 2025

If the underlying data is incomplete, inconsistent, or delayed, even the most advanced AI models and business intelligence systems will produce unreliable insights. Siloed storage : Critical business data is often locked away in disconnected databases, preventing a unified view. But theyre only as good as the data they rely on.

High Quality Data 52

High Quality Data Business Intelligence Unstructured Data Data Pipeline 52

Cloudyard

DECEMBER 24, 2024

In this blog, well explore Building an ETL Pipeline with Snowpark by simulating a scenario where commerce data flows through distinct data layersRAW, SILVER, and GOLDEN.These tables form the foundation for insightful analytics and robust business intelligence. Built clean, enriched datasets in the SILVER layer.

Building 52

Building Raw Data Scala Business Intelligence 52

Edureka

JANUARY 21, 2025

First, navigate to Table View The dataset labeled “sample dataset” is shown below. Data Measure = CALCULATE ( SUM ( 'sample dataset'[Revenue] )) 6. Data Measure = CALCULATE ( SUM ( 'sample dataset'[Revenue] ), FILTER ( 7. Data Measure = CALCULATE ( SUM ( 'sample dataset'[Revenue] ), FILTER ( ALL ( 8.

BI 52

BI Datasets Business Intelligence Certification 52

Knowledge Hut

MAY 29, 2024

The choice of datasets is crucial for creating impactful visualizations. Economic data, including GDP and employment rates, identify economic patterns and business opportunities. The dataset selection depends on goals, context, and domain, with considerations for data quality, relevance, and ethics. Census Bureau The U.S.

Datasets 52

Datasets Transportation Entertainment Media 52

Knowledge Hut

DECEMBER 26, 2023

The strategic, tactical, and operational business decisions of a company are directly impacted by Business intelligence. Learn all about Business Intelligence and Visualization training and earn business intelligence certifications. What is Business Intelligence (BI)?

Business Intelligence 52

Business Intelligence BI Data Mining Data Analysis 52

Knowledge Hut

JULY 31, 2023

In 2023, Business Intelligence (BI) is a rapidly evolving field focusing on data collection, analysis, and interpretation to enhance decision-making in organizations. You can gain expertise from international experts in Tableau, BI, TIBCO, and Data Visualization through Business Intelligence and Visualization training.

Business Intelligence 52

Business Intelligence BI Data Mining Data Collection 52

U-Next

AUGUST 11, 2022

Ultimately, to make decisions that are both sustainable and lucrative, organizations and businesses require specific assistance. Any business user may quickly resolve difficulties using current and skilled Business Intelligence (BI) technologies, even without intensive IT participation.

Business Intelligence 40

Business Intelligence BI Unstructured Data Programming 40

Advancing Analytics: Data Engineering

JULY 2, 2019

This means that the business intelligence function of “ETL Developer” is finding itself faced with this new selection of technologies and the rich history of big data architectural patterns and pitfalls they need to learn. But note… it’s not everything that we expect a Business Intelligence developer to be.

Business Intelligence 52

Business Intelligence Data Engineer Data Engineering Engineering 52

ThoughtSpot

JUNE 26, 2023

Today I’m excited to announce our $200M acquisition of Mode , the modern Business Intelligence (BI) platform, to help your data teams confidently and quickly bring generative AI capabilities to business users throughout your organization without ever breaking a sweat. Robust, reusable data models.

BI 105

BI Business Intelligence Datasets Government 105

RandomTrees

MARCH 10, 2025

Cloud-Based Solutions: Large datasets may be effectively stored and analysed using cloud platforms. Predictive analytics and business intelligence (BI) solutions transform raw data into actionable insights, including real-time dashboards, forecasting capabilities, and scenario modelling.

Retail 52

Retail Hospitality Data Governance Banking 52

Maxime Beauchemin

AUGUST 28, 2017

It’s the task of the business intelligence (now data engineering) teams to solve these issues with methodologies that enforces consensus, like Master Data Management (MDM), data integration , and an ambitious data warehousing program.

Data Engineer 174

Data Engineer Data Engineering Engineering Software Engineering 174

dbt Developer Hub

APRIL 20, 2025

dbt is the standard for creating governed, trustworthy datasets on top of your structured data. In particular, we expect both Business Intelligence and Data Engineering will be driven by AI operating on top of the context defined in your dbt Projects. Today, we are open sourcing an experimental version of the dbt MCP server.

Structured Data 98

Structured Data SQL BI Project 98

Edureka

APRIL 14, 2025

This blog breaks down how these tools complement and differ from one another to help you identify the best fit for your business. Understanding the Tools One platform is designed primarily for business intelligence, offering intuitive ways to connect to various data sources, build interactive dashboards, and share insights.

BI 40

BI Business Intelligence Raw Data Retail 40

Knowledge Hut

JANUARY 24, 2024

Power BI takes advantage of Microsoft's business analytics. The business intelligence market has multiplied in recent years and is anticipated to do so going forward. You should be data-driven if you want to pursue your career in Business Intelligence, Analytics, or Data Science.

BI 98

BI Business Intelligence Non-relational Database Machine Learning 98

Scott Logic

MARCH 25, 2024

We, Mike Morgan and Steve Conway, are a pair of Senior Developers at Scott Logic who have recently been evaluating Business Intelligence tools. Tableau is a platform of services and prides itself on being a market leader in business intelligence ( article ).

BI 52

BI Business Intelligence Cloud AWS 52

Knowledge Hut

DECEMBER 26, 2023

Along with business understanding, you also need to have analytical skills. These skills are essential to collect, clean, analyze, process and manage large amounts of data to find trends and patterns in the dataset. The dataset can be either structured or unstructured or both.

Data Science 97

Data Science BI Machine Learning Business Intelligence 97

Data Engineering Weekly

FEBRUARY 2, 2025

DeepSeek development involves a unique training recipe that generates a large dataset of long chain-of-thought reasoning examples, utilizes an interim high-quality reasoning model, and employs large-scale reinforcement learning (RL). Many articles explain how DeepSeek works, and I found the illustrated example much simpler to understand.

Data Engineer 57

Data Engineer Data Engineering Engineering Data Lake 57

Data Engineering Podcast

NOVEMBER 20, 2022

Push information about data freshness and quality to your business intelligence, automatically scale up and down your warehouse based on usage patterns, and let the bots answer those questions in Slack so that the humans can focus on delivering real value.

Systems 130

Systems Metadata Data Pipeline MongoDB 130

Towards Data Science

NOVEMBER 4, 2023

Does your DE work well enough to fuel advanced data pipelines and Business intelligence (BI)? Indeed, datalakes can store all types of data including unstructured ones and we still need to be able to analyse these datasets. I’d like to discuss some popular Data engineering questions: Modern data engineering (DE). What is it?

Data Engineer 98

Data Engineer Data Engineering Engineering BI 98

Monte Carlo

JULY 30, 2024

By ensuring these data quality dimensions are met, data teams can better support downstream business intelligence use cases, building data trust. The six dimensions of data quality are accuracy, completeness, integrity, validity, timeliness, and uniqueness. What are the 7 Data Quality Dimensions?

Data Validation 96

Data Validation Datasets Medical Raw Data 96

ThoughtSpot

APRIL 7, 2025

Everyone associated with Business Intelligence (BI) applications is talking about their Artificial Intelligence (AI) journey and the integration of AI in analytics. Artificial intelligence encompasses a broad spectrum of categories, including machine learning, natural language processing, computer vision, and automated insights.

Metadata 52

Metadata Algorithm BI Machine Learning 52

Cloudera

AUGUST 17, 2021

DE, DW, and ML practitioners that want to orchestrate multi-step data pipelines in the cloud, using a combination of Spark and Hive, can now generate curated datasets for use by downstream applications efficiently and securely. Let’s take a common use-case for Business Intelligence reporting. CDP Airflow operators.

Data Pipeline 115

Data Pipeline Management BI Python 115

Knowledge Hut

DECEMBER 29, 2023

Big Data is a part of this umbrella term, which encompasses Data Warehousing and Business Intelligence as well. It's possible that having these abilities can help you assist others in your business in accessing and interpreting information more effectively.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

Knowledge Hut

DECEMBER 22, 2023

Power BI is a technology-driven business intelligence tool or an array of software services, apps, and connectors to convert unrelated and raw data into visually immersive, coherent, actionable, and interactive insights and information. Microsoft developed it and combines business analytics, data visualization, and best practices.

BI 98

BI Business Intelligence Machine Learning SQL 98

Cloudera

FEBRUARY 8, 2021

Curated, quality datasets are the backbone of any advanced analytics initiative. CDE will then make the data available to Cloudera Data Warehouse (CDW), where it will be made available for advanced analytics and business intelligence reports. The CDE steps are outlined below. 2 ECC data enrichment pipeline.

Data Pipeline 118

Data Pipeline Building Manufacturing Data Warehouse 118

Precisely

FEBRUARY 17, 2025

Much of my career has been spent building data to accurately locate addresses for business intelligence (at GDT and Pitney Bowes) or navigation (at Tele Atlas and TomTom). At Precisely, we’re investing in integrated address and property datasets to help manage this complexity.

Telecommunication 58

Telecommunication Utilities Business Intelligence Education 58

Knowledge Hut

JANUARY 3, 2024

Obtaining Business Intelligence Training will assist you in gaining key insight into the data through different graphical representations. Importing And Cleaning Data This is an important step as a perfect and clean dataset is required for distinct and perfect data visualization. Can Python be used for data visualization?

Python 98

Python Programming Language Datasets Data Science 98

ThoughtSpot

JANUARY 31, 2024

It’s an exciting time to be in the world of data and business intelligence. ThoughtSpot joined forces with Mode in June 2023 to deliver one platform that serves the full spectrum of business intelligence users. Some will always love getting hands-on with data—but that’s no longer the only option.

BI 106

BI Business Intelligence Machine Learning Data 106

Precisely

SEPTEMBER 25, 2023

When it comes to third-party data, you just need to find the best quality data and sources that deliver the results you need – whether you’re using that information for business intelligence dashboards, problem-solving, analytics, or AI/ML applications. What perspectives and opportunities could you uncover?

Data Validation 99

Data Validation Process Raw Data Data Cleanse 99

Knowledge Hut

DECEMBER 26, 2023

A simple usage of Business Intelligence (BI) would be enough to analyze such datasets. Business Intelligence tools, therefore cannot process this vast spectrum of data alone, hence we need advanced algorithms and analytical tools to gather insights from these data. What is the need for Data Science?

Data Engineer 98

Data Engineer Data Engineering Engineering Hadoop 98

AltexSoft

OCTOBER 30, 2021

Data scientist’s responsibilities — Datasets and Models. When a business seeks to extract value from data, the first person it needs to talk to is a data scientist. A data scientist splits the dataset into three subsets — for training, testing, and validation. Let’s explore it. Model training.

Data Engineer 98

Data Engineer Data Engineering Engineering Machine Learning 98